Triple
T13075870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barabanki district |
E329570
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Haidergarh
Haidergarh is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and agricultural surroundings.
|
E1041826
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Haidergarh | Statement: [Barabanki district, hasTown, Haidergarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haidergarh Context triple: [Barabanki district, hasTown, Haidergarh]
-
A.
Kishangarh
Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
-
B.
Shakargarh
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
-
C.
Randhawa
Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
-
D.
Barwala
Barwala is a prominent town in the Hisar district of Haryana, India, known as a local commercial and administrative center for surrounding rural areas.
-
E.
Rikhawdar
Rikhawdar is a town in Myanmar located along the India–Myanmar border, serving as a key local hub for cross-border trade and movement.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Haidergarh Triple: [Barabanki district, hasTown, Haidergarh]
Generated description
Haidergarh is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and agricultural surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haidergarh Target entity description: Haidergarh is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and agricultural surroundings.
-
A.
Kishangarh
Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
-
B.
Shakargarh
Shakargarh is a town in Punjab, Pakistan, known for its agricultural surroundings and proximity to the border with India.
-
C.
Randhawa
Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
-
D.
Barwala
Barwala is a prominent town in the Hisar district of Haryana, India, known as a local commercial and administrative center for surrounding rural areas.
-
E.
Rikhawdar
Rikhawdar is a town in Myanmar located along the India–Myanmar border, serving as a key local hub for cross-border trade and movement.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98117209081908272021013df2222 |
completed | April 10, 2026, 11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7460c05bc819089cdd004bb07c492 |
completed | May 3, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_69f749ffd5d4819096cee1b27838d7d3 |
completed | May 3, 2026, 1:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f74a58aa948190978568028cc5a445 |
completed | May 3, 2026, 1:15 p.m. |
Created at: April 9, 2026, 9:01 p.m.